Las Sendas del cambio tecnológico en la agricultura española contemporánea

Los procesos de cambio técnico en la agricultura no se han empezado a tratar de forma directa hasta fechas recientes. Con frecuencia, además, su tratamiento ha estado condicionado por supuestos y consideraciones que no permiten explicar las causas que los impulsaron ni sus características diferenciales, ya sea por aceptar acríticamente los postulados neoclásicos de la teoría económica o por utilizar unos referentes sobre las posibilidades de innovación y el comportamiento de los agentes económicos, poco adaptados a la diversidad de realidades agrarias. En primer lugar, que la evolución del cambio técnico en la agricultura española ha estado caracterizada por la coexistencia de procesos contínuos y discontínuos de diferente entidad y, por tanto, por la coexistencia de complejas líneas de conexión entre las diversas ofertas tecnológicas que se han ido articulando a lo largo del tiempo y la eclosión de cambios técnicos radicales. En segundo lugar, pondremos de relieve la existencia de constelaciones técnicas diferenciadas para los diversos ámbitos ambientales del Estado Español, especialmente para el período anterior a 1936, y la significativa ampliación que experimentaron seguidamente las posibilidades reales de innovación desde mediados del siglo XX, con la difusión de las nuevas técnicas de la Revolución Verde. Por último y con respecto a las circunstancias que han impulsando la transformación del sector agrario español hasta el momento presente, destacaramos la política económica del Estado y la actividad de las instituciones públicas, identificables con lo que se conoce hoy en día como sistema nacional de innovación.

La nissaga dels gassió com a exemple de la pagesia benestant

Aquest treball s'ha proposat conèixer la manera com van afectar els petits fets de la història un grup concret de la societat, precisament el més majoritari, la pagesia, per mitjà de l'estudi de diverses facetes de la seva existència.

A multi-objective model for a multi-period distribution management problem

The problems arising in commercial distribution are complex and involve several players and decision levels. One important decision is relatedwith the design of the routes to distribute the products, in an efficient and inexpensive way.This article deals with a complex vehicle routing problem that can beseen as a new extension of the basic vehicle routing problem. The proposed model is a multi-objective combinatorial optimization problemthat considers three objectives and multiple periods, which models in a closer way the real distribution problems. The first objective is costminimization, the second is balancing work levels and the third is amarketing objective. An application of the model on a small example, with5 clients and 3 days, is presented. The results of the model show the complexity of solving multi-objective combinatorial optimization problems and the contradiction between the several distribution management objective.

Modelling leaf development in Oxalis latifolia

This study was carried to develop functions that could explain the growth of Oxalis latifolia, in both early stages and throughout the season, contributing to the improvement of its cultural control. Bulbs of the Cornwall form of O. latifolia were buried at 1 and 8 cm in March 1999 and 2000. Samples were destructive at fixed times, and at each time the corresponding BBCH scale codes as well as the absolute number of growing and adult leaves were noted. Using the absolute number of adult leaves (transformed to percentages), a Gaussian curve of three parameters that explains the growth during the season (R2=0.9355) was developed. The BBCH scale permitted the fit of two regression lines that were accurately adjusted for each burial depth (R2=0.9969 and R2=0.9930 respectively for 1 and 8 cm). The best moment for an early defoliation in Northern Spain could be calculated with these regression lines, and was found to be the second week of May. In addition, it was observed that a burial depth of 8 cm does not affect the growing pattern of the weed, but it affects the number of leaves they produce, which decreases to less than a half of those produced at 1 cm.

Discriminating crop, weeds and soil surface with a terrestrial LIDAR sensor

In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and weeds from soil surface was done. The study continues a previous work carried out in a maize field in Spain with a LIDAR sensor using exclusively one index, the height profile. The current system uses a combination of the two mentioned indexes. The experiment was carried out in a maize field at growth stage 12–14, at 16 different locations selected to represent the widest possible density of three weeds: Echinochloa crus-galli (L.) P.Beauv., Lamium purpureum L., Galium aparine L.and Veronica persica Poir.. A terrestrial LIDAR sensor was mounted on a tripod pointing to the inter-row area, with its horizontal axis and the field of view pointing vertically downwards to the ground, scanning a vertical plane with the potential presence of vegetation. Immediately after the LIDAR data acquisition (distances and reflection measurements), actual heights of plants were estimated using an appropriate methodology. For that purpose, digital images were taken of each sampled area. Data showed a high correlation between LIDAR measured height and actual plant heights (R2 = 0.75). Binary logistic regression between weed presence/absence and the sensor readings (LIDAR height and reflection values) was used to validate the accuracy of the sensor. This permitted the discrimination of vegetation from the ground with an accuracy of up to 95%. In addition, a Canonical Discrimination Analysis (CDA) was able to discriminate mostly between soil and vegetation and, to a far lesser extent, between crop and weeds. The studied methodology arises as a good system for weed detection, which in combination with other principles, such as vision-based technologies, could improve the efficiency and accuracy of herbicide spraying.